This paper aims to investigate the causal links among export diversification, per capita income, and energy demand for 20 Asia-Pacific Economic Cooperation (APEC) countries. Human capital, industry share, and Foreign Direct Investments (FDI) are included within a multivariate framework. Using data covering the 1995–2018 period, an innovative sequential Artificial Neural Networks experiment is developed. Empirical results highlight that the export diversification index negatively affects the neural target corresponding to energy demand. Conversely, per capita GDP displays a significant influence on the acceleration of the same energy target. Hence, findings suggest that export diversification plays a mitigating role in the demand for energy, which is congruent with the literature. Moreover, economic growth is found to be substantially driven by export diversification, while no evidence of a causal effect is found among export diversification, human capital, and FDI. Such inferences are finally corroborated by a Decision Tree model, conducted as a final robustness check. In line with the Sustainable Development Goals (SDGs), adequate measures are suggested to improve energy savings along the supply chain, without hindering the economic performance of the Asian region.

Magazzino, C., Mele, M., Schneider, N., & Shahzad, U. (2022). Does Export Product Diversification Spur Energy Demand in the APEC region? Application of a New Neural Networks Experiment and a Decision Tree Model. ENERGY AND BUILDINGS, 258(111820) [10.1016/j.enbuild.2021.111820].

Does Export Product Diversification Spur Energy Demand in the APEC region? Application of a New Neural Networks Experiment and a Decision Tree Model

Magazzino, Cosimo
;
Mele, Marco;
2022

Abstract

This paper aims to investigate the causal links among export diversification, per capita income, and energy demand for 20 Asia-Pacific Economic Cooperation (APEC) countries. Human capital, industry share, and Foreign Direct Investments (FDI) are included within a multivariate framework. Using data covering the 1995–2018 period, an innovative sequential Artificial Neural Networks experiment is developed. Empirical results highlight that the export diversification index negatively affects the neural target corresponding to energy demand. Conversely, per capita GDP displays a significant influence on the acceleration of the same energy target. Hence, findings suggest that export diversification plays a mitigating role in the demand for energy, which is congruent with the literature. Moreover, economic growth is found to be substantially driven by export diversification, while no evidence of a causal effect is found among export diversification, human capital, and FDI. Such inferences are finally corroborated by a Decision Tree model, conducted as a final robustness check. In line with the Sustainable Development Goals (SDGs), adequate measures are suggested to improve energy savings along the supply chain, without hindering the economic performance of the Asian region.
Magazzino, C., Mele, M., Schneider, N., & Shahzad, U. (2022). Does Export Product Diversification Spur Energy Demand in the APEC region? Application of a New Neural Networks Experiment and a Decision Tree Model. ENERGY AND BUILDINGS, 258(111820) [10.1016/j.enbuild.2021.111820].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/397523
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